lstm - Many to one implementation in keras -


i trying implement many 1 model inputs word vectors of size d . need output vector of size d @ end of lstm .

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in question , mentioned use(for many 1 model)

model = sequential() model.add(lstm(1, input_shape=(timesteps, data_dim)))

i still doubtful how specify input , more importantly output dimensions in keras model

the code provided one-to-many scenario - output of size 1. if want have output of size d need try following code:

model = sequential() model.add(lstm(d, input_shape=(len_seq, d)))

moreover - word vectors advise use embedding layer designed use case. use input lstm then.


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